code: def test_load_pretrained_model_exclude(tmp_path):
      model_src = Model()
      torch.save(model_src.state_dict(), tmp_path / "model.pth")
  
      model_dst = Model()
      load_pretrained_model(
          f"{tmp_path}/model.pth:::layer2", model_dst, "cpu"
      )
  
      for k in model_dst.state_dict():
          if not k.startswith("layer2"):
              np.testing.assert_array_equal(
                  model_dst.state_dict()[k].numpy(),
                  model_src.state_dict()[k].numpy(),
              )
  
file_path: espnet/test/espnet2/torch_utils/test_load_pretrained_model.py
imports: import numpy
  import torch
  from espnet2.torch_utils.load_pretrained_model import load_pretrained_model
label_desc: Use image node_id 3 for calling a global function with example usage: test_load_pretrained_model_exclude(tmp_path) without return types